Dejar que ChatGPT piense por nosotros podría tener un coste para el cerebro, según un estudio - La Vanguardia
Dejar que ChatGPT piense por nosotros podría tener un coste para el cerebro, según un estudio La Vanguardia
Dejar que ChatGPT piense por nosotros podría tener un coste para el cerebro, según un estudio La Vanguardia
La IA revoluciona la Cardiología: un nuevo algoritmo permite detectar mejor el riesgo de muerte súbita consalud.es
AWS has open-sourced Dogwood, a policy language extending Cedar with temporal conditions so rules can reason about an agent's prior tool calls rather than one request in isolation. It covers approvals, rate limits and running totals, ships under Apache 2.0, and is supported in AgentCore Policy, though the reference interpreter is not production-ready. By Steef-Jan Wiggers
Amazon DynamoDB recently introduced native vector search, allowing developers to store embeddings alongside application data and run approximate nearest-neighbor queries directly from DynamoDB without using a separate vector database. The feature supports filtered similarity searches and configurable vector indexes for semantic search workloads. By Renato Losio
Nikolay Samokhvalov has developed PGSimCity, an open-source educational tool that visualises PostgreSQL mechanics as a 3D spatial simulation in the browser. It assists backend developers and site reliability engineers in understanding SQL and the dynamics of kernel execution. The project is available on GitHub and aims to enhance understanding of database architecture through interactive elements. By Olimpiu Pop
SpaceX Completes $60B Acquisition Of AI Coding Startup Cursor Bitcoin World
Latent video generation relies on autoencoders to define a compact space in which generative models operate. Although video autoencoder architectures have evolved substantially, their latent spaces are still optimized primarily for pixel-level reconstruction and provide limited high-level semantic organization. A reconstruction-optimal latent space, however, need not be well suited to generative modeling.
Assessing proxemic danger from a robot's egocentric perspective is critical for safe embodied navigation in human environments and requires both visual and contextual reasoning. We evaluate three opensource vision-language models (VLMs) (\textit{InternVL}, \textit{Qwen-VL}, and \textit{SmolVLM}) on the classification of egocentric robot images into four danger levels, comparing three prompting strategies and two rounds of QLoRA fine-tuning against a stratified random baseline.
Active inference offers a unified framework for perception, learning, and action, but scaling discrete active-inference models to rich spatial and temporal domains remains difficult. Renormalising generative models (RGMs) address this challenge by composing discrete generative models across spatial and temporal scales, coarse-graining lower-level states and paths into higher-level causes for objects, events, and action.
SpaceX to buy AI coding assistant Cursor for $60 billion CBS News
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